Data Engineer (Industrial IoT & SCADA Systems)

Data Engineer

Key Responsibilities

• Design and develop

  data ingestion pipelines

  for real-time

  SCADA, PLC, and IoT

  data sources.
• Implement and optimize

  timeseries databases

  (TimescaleDB, AWS Timestream, Azure Data Explorer (ADX) ) for high-frequency industrial data storage.
• Develop

  ETL workflows

  for structured and unstructured machine data, ensuring high availability and scalability.
• Perform

  data normalization, unit conversion, and noise filtering

  to enhance data quality for AI-driven analytics.
• Design

  data transformation frameworks

  to standardize industrial protocols (Modbus, OPC-UA, BACnet, Profibus).
• Collaborate with

  AI & Analytics teams

  to prepare datasets for predictive maintenance, anomaly detection, and process optimization.
• Work closely with

  SCADA engineers

  to ensure seamless integration between industrial control systems and enterprise data platforms.
• Implement

  data governance, security, and compliance

  following

  ISA/IEC 62443 and NIST CSF

  best practices.
• Monitor, troubleshoot, and optimize data pipelines to ensure low latency and high reliability.

Required Skills & Experience

• 5-7 years

  of experience as a

  Data Engineer

  in an industrial/IIoT environment.
• Proficiency in

  Time-Series Databases

  (TimescaleDB, AWS Timestream, InfluxDB, Azure Data Explorer (ADX).
• Strong knowledge of

  ETL pipelines, data transformation, and real-time data streaming

  (Kafka, Apache Flink, IoT Hub, AWS Kinesis).
• Experience with

  data normalization, filtering, and unit conversions

  in industrial automation.
• Hands-on experience with

  SCADA systems

  (Ignition, Wonderware, WinCC) and

  PLC communication

  (Siemens, Rockwell, ABB).
• Familiarity with

  IoT protocols

  (MQTT, OPC-UA, Modbus, Profibus, EtherNet/IP).
• Strong SQL and Python skills for

  data processing, querying, and automation

  .
• Experience in

  containerized environments

  (Docker, Kubernetes) and cloud-based

  data solutions

  (AWS, Azure, GCP).
• Knowledge of

  industrial cybersecurity standards

  (ISA 62443, NIST CSF) is a plus.

Preferred Qualifications

• Experience with

  real-time anomaly detection and predictive maintenance

  using AI/ML.
• Familiarity with

  Manufacturing Execution Systems (MES)

  and

  ERP integration

  (SAP, Microsoft Dynamics).
• Knowledge of

  Edge Computing frameworks

  for industrial applications.